Over the last decade, a number of application domains, going from
online advertising [1]}, [2]} to mobile health [3]}, [4]}, have embraced and led the way in the use of multi-armed bandit (MAB) algorithms to conduct adaptive experimentation. Such algorithms can substantially improve performance in terms of particular objectives, such as achieving optimal asymptotic regret bounds  [5]}, [6]}.
